I imagine that there must be some system similar to prolog but with a probabilistic model of inference, for example ground rules could be sorted by statistical properties to accelerate inference. Just like machine learning trees select features for classification (perhaps using cross-entropy minimization).

Edit: I found Journal of Machine Learning Research 7 (2006) 307–342, Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting